Investigative Statistical Analysis - Analyzing Accuracy in Data Presentation

  • Guided Project
  • 0.9 hours
  • Intermediate
  • Python

Practice statistical analysis in Python to investigate movie rating bias and determine if Fandango inflated ratings.

Overview

In this project, you'll assume the role of a data journalist to investigate potential bias in Fandango's movie rating system. Applying your Python skills, you'll statistically analyze movie ratings data to determine if there's a significant difference between Fandango's ratings and other rating systems. This project allows you to develop your data analysis skills in a real-world context. You'll learn to critically examine data sampling methods, compare frequency distributions, and draw meaningful conclusions from statistical metrics. These techniques will enhance your ability to uncover insights and trends in various datasets. Objective: Analyze movie ratings data using Python and statistical analysis to determine if Fandango inflated ratings after a previous analysis revealed bias in their rating system.

What You'll Learn

  • How to clean and prepare datasets for statistical comparison
  • How to visualize and interpret rating distributions
  • How to use frequency tables and summary statistics to reveal data patterns
  • How to draw conclusions from data and understand its limitations
  • How to organize your analysis workflow in a Jupyter Notebook

Before You Start

  • Employing various sampling methods to sample data
  • Measuring variables in statistics
  • Identifying different types of variables
  • Generating frequency distribution tables
  • Creating visualizations to display frequency distributions

Project Steps

8 steps

  1. 1 Did Fandango Inflate Movie Ratings?
  2. 2 Understanding the Data
  3. 3 Changing the Goal of our Analysis
  4. 4 Isolating the Samples We Need
  5. 5 Comparing Distribution Shapes for 2015 and 2016
  6. 6 Comparing Relative Frequencies
  7. 7 Determining the Direction of the Change
  8. 8 Next steps

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